dlaperriere

docker-images

promscale

[DEPRECATED] Promscale is a unified metric and trace observability backend for Prometheus, Jaeger and OpenTelemetry built on PostgreSQL and TimescaleDB.

pipelines

Machine Learning Pipelines for Kubeflow

reader

A Python feed reader library.

gensim

Topic Modelling for Humans

socialsentiment

Sentiment Analysis application created with Python and Dash, hosted at socialsentiment.net

grafana

The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.

grafanalib

Python library for building Grafana dashboards

voila

Voilà turns Jupyter notebooks into standalone web applications

node-red

Low-code programming for event-driven applications

ipywidgets

Interactive Widgets for the Jupyter Notebook

mpld3

An interactive data visualization tool which brings matplotlib graphics to the browser using D3.

Tx

Tx (LINQ to Events)

RxPY

ReactiveX for Python

RxCpp

Reactive Extensions for C++

raw

The missing link between spreadsheets and data visualization

pubmed_parser

:clipboard: A Python Parser for PubMed Open-Access XML Subset and MEDLINE XML Dataset

bartCause

Causal Inference using Bayesian Additive Regression Trees

ranger

A Fast Implementation of Random Forests

grf

Generalized Random Forests

EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

causalml

Uplift modeling and causal inference with machine learning algorithms

ips4o

In-place Parallel Super Scalar Samplesort (IPS⁴o)

ips4o

In-place Parallel Super Scalar Samplesort (IPS⁴o)

pdqsort

Pattern-defeating quicksort.

shapr

Explaining the output of machine learning models with more accurately estimated Shapley values

fastshap

Fast approximate Shapley values in R

shap

A game theoretic approach to explain the output of any machine learning model.

reticulate

R Interface to Python